The present application relates to electron channeling contrast imaging (ECCI) of a crystalline material. More particularly, the present application relates to a method that employs image recognition and processing techniques to identify defects obtained by ECCI of a crystalline material for automatic characterization.
In the manufacturing of microelectronics, defects in the crystalline quality of the material can adversely affect the material quality. As materials (such as, Ge, SiGe and/or III-V compound semiconductors) are added into the manufacturing line, defects caused by the epitaxy and processing of dissimilar materials are more abundant than with silicon only technologies. Therefore, it is important to test the defect density and other properties in the materials to control the growth and processing in the line.
Most of the conventional techniques used for such defect detection such as, for example, TEM, are destructive, since they require cutting, polishing and/or thinning of the sample being tested. Although there are some non-destructive techniques for defect detection, such techniques are limited. For example, known non-destructive techniques such as, for example, electron channeling contrast imaging (ECCI), have low throughput, which hinders the ability of the known non-destructive techniques for providing accurate and efficient defect detection.
In view of the above, there is a need for providing a way to use ECCI for in-line microelectronics metrology of crystalline defects for crystalline semiconductor materials such as, for example, germanium (Ge), silicon germanium alloys (SiGe), or III-V compound semiconductors.